Learning postures through an imitation game between a human and a robot

In this paper, we investigate a sensory-motor architecture allowing a robot to learn to recognize postures. The learning is performed without a teaching signal that associates a specific posture with the robot's motor internal state. Our architecture assumes that the robot initially performs postures, then the human imitates them. An on-line learning scheme without an explicit reward or ad-hoc detection mechanism or a formatted teaching technique is proposed. Investigations on how a "naive" system can learn to imitate correctly another person's posture during a natural interaction motivate the current research work.